1. Stop the alien invasion: detection and control of Ailanthus Altissima


Ailanthus altissima is one of the worst invasive plant species in Europe. It reproduces both by seeds and asexually by vegetative sprouts. The winged seed can be dispersed by wind, water and machinery, while its robust root system can generate numerous suckers and progenity plants. A. altissima typically occurs in very dense clumps, resulting from even-aged seedling establishment or from clonal expansion through root sprouting, and occasionally it growth as widely spaced or single stems.
It grows on a broad range of anthropogenic to natural sites, from stony and sterile soils to rich alluvial bottoms. Due to its vigour, rapid growth, tolerance, adaptability and lack of natural enemies, it spreads spontaneously out-competing other plant species and reducing their growth. 
In the last decades, the species is quickly spreading and multiplying in the Alta Murgia national Park (South Italy) mostly characterized by dry grassland and pseudo-steppe, wide-open spaces with low vegetation, whose tendency is to be easily invaded. Ailanthus altissima causes serious direct and indirect damages to ecosystems, replacing and altering communities that have a great conservation value, producing severe ecological environmental and economic effects and causing natural habitat loss and degradation. This treat is likely to increase in the future, unless robust action is taken at all levels to control the advancement and spread.  In a recent working document  of the European Commission, it has been evidenced that the costs of controlling and eliminating invasive species in Europe amounts to 12 billion of euro per year. Two relevant questions then arises: whether it is possible or not to fully eradicate or at least to reduce the impact of an invasive species and how to do that at a minimum cost, in terms of both environmental damage and economic resources.
The Life Programme, the European Commission financial instrument for environmental and nature conservation, funded the Life Alta Murgia project (LIFE12BIO/IT/000213) which has, as main objective, the eradication of the invasive exotic tree species from the Alta Murgia national Park and which provided both the expert knowledge and the infield data for the case study we have started.
Actually, there is a single map of Ailanthus A.  presence, provided by the Life Alta Murgia project, and it is dated at 2012, before the starting  of the on-going  eradication program. Due to the lack of data, predicting the extent of invasion and its impacts are extremely difficult as well as assessing the efficacy of any control measures. 
If static models based on statistical fitting cannot predict any spatial–temporal dynamics, (e.g. where and when the Ailanthus trees may repopulate a zone), mechanistic models which incorporate growth and spread of a plant, would require a precise parametrization that is extremely difficult with the few available data. Due to these limitations, we rely on a relatively simple mechanistic model, a diffusion model, which is validated against the current plant spatial distribution deduced by satellite images. The effect of an eradication program is taken into account with a reaction term, which simulates the plant eradication during a control program.
The value of our predictive mechanistic model would be to provide an automatic tool for an a-priori estimate of the effectiveness of a planned control action under temporal and budget constraints. In our study, the interest is focused on finding the best budget allocation both in space and in time for the Park area maintenance, this aiding in determining whether a control policy needs to be improved.  
Within the activities of the ECOPOTENTIAL H2020 project, we developed an automatic tool that can get the plant presence information from the satellite and use that information for predicting the best action of the park manager. Indeed, many satellite data are not being used to their full potential and there are optimisation methods that are powerful but not being used on-ground. We are linking the two methods and providing an avenue to make them accessible and useful to managers.
We are currently estimating the uncertainty of the model and working at a validation of the overall approach by testing it on different areas, by using aerial images coming from a regional project.
The final aim is to provide a robust tool to be easily transferred to other geographical areas and potentially to different species. The approach might incorporate the effect of changes (climate, land cover): this is still an open research issue, which will largely benefit from the exploitation of the LifeWatch ERIC infrastructure. 

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